Cognitive radio is a telecommunications system capable of configuring its radio parameters as a function of its environment.
A promising application of cognitive radio comprises improving occupation of the spectrum using the use of the dynamic spectrum.
Cognitive radio can detect if a portion of the spectrum is being used or not and temporarily occupy it without creating interference for other users.
As for any radio frequency system, cognitive radio must comply with the rules stipulated by the organisms regulating the spectrum.
Today, these organisms (especially the Federal Communications Commission (FCC) in the USA) are starting to authorise use of cognitive radio in the bands freed up by the dividende digital. Reference can be made to the document FCC: Second Memorandum Opinion and Order, September 2010, which mentions empty space between coverage zones of television stations (in English, TV white space).
In UHF bands (that is, Ultra-High Frequency, frequencies are between 300 MHz and 3000 MHz, especially between 470 MHz and 790 MHz (TV-UHF bands)) primary users, that is, users granted an access license to the spectrum, are digital television and wireless microphones. It is envisaged that these primary users are prioritised relative to the new cognitive systems. Sharing the spectrum is therefore done by prioritising the quality of service and therefore the signal of these primary users. It can be said that the primary system has to be protected from secondary cognitive systems. In practice, primary users correspond to users having priority access to the spectrum.
If digital television systems can be protected efficaciously by defining a database and its consultation by geolocalisation, this solution is difficult to apply to wireless microphones, as their large number and their random deployment make it impossible to update a database.
Spectrum detection is therefore always the solution for protecting microphones.
Contrary to detection of digital television signals which can utilise the cyclostationary characteristics of OFDM modulation, detecting the spectrum of wireless microphones is difficult due to the few characteristics a priori of its signal.
Solutions based on blind detectors are known (see document H,-S. Chen, W., Gao, and D. Daut, Spectrum sensing for wireless microphone signals, IEEE Sensor, Mesh and Ad Hoc Communications and Networks Workshops (SECON08), June 2008). These solutions are based on eigenvalue decomposition (see document S. Xu, Y. Shane, and H. Wang, SVD based Sensing of a Wireless Microphone Signal in Cognitive Radio Networks, IEEE International Conference on Communications Systems, November 2008), spectral correlation (see document N. Han, S. M. Shon, J. O. Joo, and J. M. Kim, “Spectral correlation-based signal detection method for spectrum sensing in IEEE 802.22 systems, International Conference on Advanced Communication Technology, February 2006) or an energy detector (see document M. Ghosh, V. Gaddam, G. Turkenich, and K. Chaiiapali, Spectrum-Sensing Prototype for Sensing ATSC and Wireless Microphone Signals, International Conference on Cognitive Radio Oriented Wireless Networks and Communications (CROWNCOM08), May 2008).
One of the properties common to these algorithms is that they presuppose the detection of broadband signals. However, the European television hand comprises 48 channels of 8 MHz of bandwidth. Each band must be analysed to detect microphones. Their detection is therefore carried out in a narrowband context if the spectral occupation of the microphones (around 100-200 kHz) is compared to the width of a channel UHF (8 MHz).
Broadband solutions are known for resolving this problem.
Document WO 2009130372 describes such a bandwidth solution for detecting a narrowband signal.
Known broadband solutions have been dissatisfactory and are not precise enough.
There is consequently a need for proposing a solution for detecting a signal in a signal bandwidth.